Albert-Ĺaszló Barabási

The aging genome exhibits organized vulnerability to somatic mutations

This study identifies organized vulnerability in the aging genome, showing that certain genes and pathways are less mutated while others accumulate more mutations, suggesting a network-based mechanism for cellular decline.

NetMedPy: A Python package for Large-Scale Network Medicine Screening

NetMedPy provides a computational package for efficient Network Medicine analyses, supporting diverse scoring functions and metrics for large-scale molecular screening.

Physical Network Constraints Define the Lognormal Architecture of the Brain's Connectome

The paper analyzes eight connectomes and finds their degree distributions follow lognormal patterns, attributing this to a stochastic multiplicative process governing neuron size.

Negative Selection Allows DNA Mismatch Repair-Deficient Mouse Fibroblasts In Vitro to Tolerate High Levels of Somatic Mutations

This study shows that DNA mismatch repair-deficient mouse fibroblasts can tolerate high mutation burdens in vitro without significant growth effects, revealing mutation-driven population changes and negative selection.

Genomics-based annotations help unveil the molecular composition of edible plants

The paper uses genome-associated functional annotations and metabolomics to predict and validate chemical compounds in edible plants, identifying novel compounds in corn.

Assessment of community efforts to advance computational prediction of protein-protein interactions

The paper evaluates 24 network-based methods for predicting protein-protein interactions across five interactomes, identifies top-performing methods, and validates their predictions experimentally.

Exploring Food Contents in Scientific Literature with FoodMine

FoodMine identifies scientific papers on garlic and cocoa chemical composition, finds extensive unstructured data on food chemicals, and creates embeddings showing health relevance.

Network Medicine Framework Shows Proximity of Polyphenol Targets and Disease Proteins is Predictive of the Therapeutic Effects of Polyphenols

The paper develops a network medicine framework to predict polyphenol therapeutic effects by analyzing the proximity of their protein targets to disease proteins in the human interactome.

Network-based prediction of protein interactions

The paper challenges the Triadic Closure Principle in protein interaction prediction and introduces the L3 principle, which outperforms existing methods and identifies novel interactions.

Predicting perturbation patterns from the topology of biological networks

The paper predicts biochemical perturbation patterns using network topology, achieving 65-80% accuracy without kinetic parameters.

Controllability in an islet specific regulatory network identifies the transcriptional factor NFATC4, which regulates Type 2 Diabetes associated genes

The paper identifies NFATC4 as a key regulator of Type 2 Diabetes genes by analyzing a gene regulatory network in pancreatic islets and linking it to eQTLs and differential expression.